Unlike our approach, Yin and Shen [1]} considered word embedding to be an implicit matrix factorization problem [2]}, and approached the issue by deciding the rank of the component matrix. Their work was conducted by introducing Pairwise Inner Product (PIP) loss, a measure that evaluates the goodness of the rank of matrix factorization. The best rank is chosen to minimize a given upper bound of the PIP loss.
